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Saudi Journal of Kidney Diseases and Transplantation
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Year : 2014  |  Volume : 25  |  Issue : 4  |  Page : 774-780
Diabetic nephropathy: A strong predictor of sleep quality in hemodialysis patients

Internal Medicine Department, Nephrology Ward, Arak Medical Sciences University, Arak, Iran

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Date of Web Publication24-Jun-2014


Sleep complaints are common in hemodialysis (HD) patients. Sleep quality (SQ) is a predictor of quality of life and mortality risk in HD. The aim of this study was to examine factors that may have a role in SQ. In this cross-sectional analytic study, 138 end-stage renal disease patients receiving maintenance HD for >3 months were included. The Pittsburgh Sleep Quality Index (PSQI) was used to measure individual's SQ. Patients with a global PSQI score >5 were assumed as poor sleepers. Eighty-eight patients (64%) were classified as poor sleepers. Poor sleepers were older and more likely had diabetes. They had significantly higher serum ferritin and calcium levels and lower serum parathyroid hormone level (all P-values <0.05). The global PSQI score was positively correlated with age, serum calcium level and presence of diabetes as the underlying cause of renal failure. In the multi-variable binary regression model, presence of diabetes (Odds Ratio (OR) = 3.67, P = 0.008) and body pain (OR = 1.182, P = 0.014) were the significant independent predictors for poor SQ. Poor SQ was common among our HD patients, especially among diabetic cases and, therefore, there is a need to pay more attention to the care of this subgroup with regard to the diagnosis and management of sleep complaints.

How to cite this article:
Edalat-Nejad M, Jafarian N, Yousefichaijan P. Diabetic nephropathy: A strong predictor of sleep quality in hemodialysis patients. Saudi J Kidney Dis Transpl 2014;25:774-80

How to cite this URL:
Edalat-Nejad M, Jafarian N, Yousefichaijan P. Diabetic nephropathy: A strong predictor of sleep quality in hemodialysis patients. Saudi J Kidney Dis Transpl [serial online] 2014 [cited 2022 Oct 3];25:774-80. Available from: https://www.sjkdt.org/text.asp?2014/25/4/774/134994

   Introduction Top

In the past two decades, sleep disorders and its predicting factors in patients on main­tenance hemodialysis (HD) has attracted the attention of many researchers. According to the literature, 30-80% of HD patients have sleep disorders such as insomnia, restless leg syndrome, sleep latency and sleepiness during the day. [1],[2],[3],[4],[5],[6],[7],[8],[9],[10],[11], [12] As shown by recent studies, there is a potential association between poor sleep and lower quality of life and increased mortality. [13],[14],[15],[16],[17], [18]

In recent years, possible factors affecting sleep have been extensively studied, but some controversy existed. Some studies have shown the association between sleep problems and higher levels of urea, phosphate and para­thyroid hormone, [5],[16],[19] and even some small surveys have found sleep quality (SQ) im­provement after parathyroidectomy. [19],[20] Also, some studies corroborated the role of inflam­mation in the pathogenesis of sleep distur-bance. [21]

The large numbers of articles that are being published about sleep disorder show that, the answer to the mystery of sleep pathogenesis and predisposing factors for insomnia still remain unresolved. Therefore, this study was carried out to investigate the association of the underlying disease of kidney failure, anthropo­metric parameters and various laboratory va­lues, including parathyroid hormone (PTH) with SQ in HD patients of our university hospital.

   Subjects and Methods Top

This cross-sectional study was performed within a HD unit of the Medical Center of Vali-Asr. All patients received daytime dia­lysis, and the total hours per week varied from 11 to 12.5 h. The inclusion criteria were as follows: Patients on maintenance HD three times a week for >3 months with age >18 years and those who provided informed consent.

The exclusion criteria were as follows: Pre­sence of malignancy, active infection, uncon­trolled heart failure, poor controlled diabetes (HgbA1c ≥7.6), acute medical or surgical con­dition that required hospitalization or opera­tion within the prior month or patients with de­mentia or psychotic disorder, as diagnosed by the researcher.

All 163 patients of our university hospital center were screened for inclusion by pre­defined criteria. Finally, a total of 138 patients were enrolled in the study. This study was approved by the Research Ethics Review Committee of our university (No. 89-99-4) and informed consent was obtained from all parti­cipants.

Quality of sleep

SQ was determined by the Pittsburgh Sleep Quality Index (PSQI), a score derived by a self-rated questionnaire, consisting of 19 ques­tions. [22] The 19-question questionnaire mea­sures the SQ of the previous month. From the answers, seven components (each scored from 0 to 3) of subjective SQ, sleep latency, sleep duration, sleep efficiency, sleep disturbances, use of sleep medications and daytime dysfunc­tion were calculated. The global PSQI score was calculated (0-21) from the sum of seven component scores, with higher scores indi­cating worse SQ. A patient with a global PSQI score >5 is considered to be a bad sleeper. In this study, patients completed this question­naire by themselves or under the assistance of research nurses at the time when the HD was performed.

Other variables

For the analysis concerning pain, patients were questioned, "How much body pains have you had during the past four weeks?" Varia­tion of body pain among prevalent HD patients was on a scale of 0-10, where 0 represented the no pain and 10 represented the worst. The mean pain score was 4.8 and the median was 5. Therefore, we categorized patients with a pain score below 5 to be in the low pain group (42%) and those with a score of 5 or greater to be in the high pain group (58%).

Blood samples were collected prior to a HD session. Age, sex, cause of renal disease and hours of dialysis per week were determined by interview and chart review. Because of dia­lysis adequacy (Kt/V) variation from session to session, we used mean hours of dialysis per week for final analysis instead of once mea­sured Kt/V. All laboratory tests were performed at the reference laboratory. Serum biochemistry was measured by standard laboratory methods. Intact parathyroid hormone (iPTH) was mea­sured using the electro-chemiluminescence immunoassay. For all lab parameters, the mean of three consecutive months' values was con­sidered as baseline.

   Statistical Analysis Top

Data were summarized as the mean and standard deviation or number and percent, as appropriate. Student's t-test was used to compare the means of normally distributed variables between "good sleepers" (global PSQI ≤ 5) and "poor sleepers" (global PSQI > 5), and the Mann-Whitney U test was used for variables that were not normally distributed. Differences among categorical variables were assessed by using the χ[2] test. The bivariate correlation test was performed to determine the association of demographic and bioche­mical data, with the PSQI score. For normally distributed variables, Pearson's correlation test was used; for non-normally distributed va­riables, Spearman's correlation test was used. Multiple linear regression with forward step­wise selection was repeated for factors that reached statistical significance (P <0.1), to identify factors independently associated with SQ. Data management and analyses were carried out using the Statistical Package for Social Sciences (SPSS), version 17. The level of significance was α = 0.05 for all compa­risons.

   Results Top

Demographic data

Of 168 patients available to enter the longi­tudinal study, 32 did not meet the inclusion criteria. The remaining 138 subjects (mean age of 59 ± 15 years, 47% male) were invited to enter the cross-sectional study. The underlying cause of renal failure was diabetic nephropathy in one-third of the cases. All the subjects attended HD for 4 h three times weekly.

Global and component PSQI scores results

In 88 cases of a total of 138 patients (64%), the global score of PSQI more than 5 was con­sidered as poor SQ. Across categories, patients with poor SQ were older and they were more likely to be diabetic. Also, they may have a significantly lower serum iPTH and higher ferritin [Table 1]. Those with poor SQ also reported higher levels of body pain.
Table 1: Comparison of demographic and laboratory data between good sleepers and bad sleepers.

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There were no significant differences in SQ by gender, duration of dialysis and age. There were also no differences in SQ by level of serum albumin, serum creatinine, hematocrit and serum phosphate [Table 1].

Bivariate analysis

The correlations between the global PSQI score and the other variables are shown in [Table 2]. There were weak but still significant positive correlations between global PSQI score and age, serum calcium and presence of dia­betes. Although not statistically significant, there was a positive correlation with body pain and also negative correlation with serum iPTH and creatinine, with global PSQI score.
Table 2: Demographic and laboratory variables correlation with global PSQI score

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Multivariate analysis

Characteristics associated with greater likeli­hood of poor SQ were considered for further analysis. Thus, variables that reached a signi­ficant correlation with the global score of sleep (P <0.1) were selected for multi-variate ana­lysis. In the regression analysis, the only pre­dictive factor for the quality of sleep was dia­betes [Table 3]. The likelihood of sleep distur­bance in diabetes was 3.67-times greater versus non-diabetics (P = 0.008).
Table 3: Multivariable-adjusted odds ratio of predictors for the poor sleep quality.

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Diabetic patients compared with non-diabetic patients had more complaints on components of subjective SQ, use of sleep medications and sleep disturbances. Also, they were older and had lower serum creatinine, urea, phosphorous and iPTH [Table 4]. There were no significant differences in the presence and severity of body pain; however, there was a mild correlation between fasting sugar amount and self-rating of bodily pain (r = 0.235, P = 0.014). Also, a moderate negative correlation has been observed between fasting sugar and iPTH (r = -306, P = 0.001).
Table 4: Comparison of sleep components and laboratory data between diabetics and non-diabetics.

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   Discussion Top

Poor SQ is common among patients on main­tenance HD. We examined the prevalence of self-reported poor sleep and patient charac­teristics associated with the same. The preva­lence of poor SQ in our experience was 64%, which was consistent with the findings of other investigators. who have studied SQ among dia­lysis patients.

In addition, we investigated the association of poor SQ with the underlying cause of renal failure and certain laboratory values. Our study demonstrated that older age, diabetes and higher serum calcium were associated with poorer SQ in stable HD patients. There was also a negative correlation between iPTH and serum creatinine with poorer SQ; never­theless, the results did not reach statistical sig­nificance. Our study also showed that diabetes was the somewhat strong independent predic­tor of poor SQ. In other word, diabetes in­creases the risk of sleep disturbance 3.67 times. Majority of previous studies have repor­ted that sleep disorders are more common in diabetic patients than non-diabetic patients, except for a study done by Yoshioka et al, [1] in which they stated that it was not an inde­pendent predictive factor for poor sleep. Also, Kutner et al [9] found that body pain and neuro­pathy, which were more common in diabetics, were independent predictive factors; however; diabetes was not considered as an independent predictor of SQ. In our study, bodily pain was an independent predictor of SQ; however, severity of self-rating pain was not different in both diabetics and non-diabetics. In explaining the results obtained, we propose the possible role of some confounding factors that are usually not taken into consideration, such as medications that may have an effect on sleep such as beta-blockers as well as degree of glycemic control. As mentioned previously, despite no significant difference in the pre­sence and severity of body pain, there was a mild correlation between fasting sugar value and body pain.

Possible factors affecting sleep have been extensively studied, but some controversies still exist. However, most studies on sleep dis­orders have shown a significant association of older age with poor SQ, but Unruh et al [5] indicated otherwise. They found that sleep dis­order was more common in younger patients during the first year of dialysis. However, Sabbatini et al [3] showed that age over 50 years was an independent prognostic factor. In our study, age was not an independent predictive factor; however, the mean age was higher in patients with sleep disorders.

In our study, there was no difference in SQ by gender, which was consistent with most studies. [3],[9],[15] However, this was in contrast with the reports of Pai et al [7] and Elder et al, [16] who have reported that poor sleep was more pre­valent in the female gender.

There are some conflicting results about the relationship between phosphate level and SQ. While some studies have observed serum phosphorus to be related to poor SQ, [5],[16] others have failed to identify significant relationships between phosphorus and SQ. [9],[12] In our study, there was no statistically significant corre­lation between SQ score and serum phos­phorus or calcium-phosphate products.

Chiu et al [21] and Pai et al [7] found a significant and independent association between SQ and serum hemoglobin even after considering a va­riety of factors. However, in our study, the global PSQI score was not associated with serum albumin, hematocrit, iPTH, ferritin or duration of HD, which was consistent with the findings of most studies. [3],[5],[9],[10],[12],[15]

Some small studies have indicated the pos­sible role of iPTH in SQ in HD patients. [19],[20] De Santo et al [20] proposed that patients on HD requiring parathyroidectomy for intractable hyperparathyroidism comprise a good model for investigating the causative role of PTH on disordered sleep and, also, Esposito et al [19] have implicated that insomnia in patients with severe hyperparathyroidism is ameliorated by parathyroidectomy. As has been shown in our study, although the iPTH was significantly lower in poor sleepers, it was not an inde­pendent predictor of SQ. To justify this, it may due to the moderately negative correlation bet­ween fasting sugar and iPTH in our data analysis. Our finding was compatible with the reports of Chiu et al [21] and Elder et al. [16]

At the end, there were several limitations to this study that should be addressed. First, the only means of measuring SQ was filling out a self-rating questionnaire, and comprehensive polysomnography was not performed. Second, the possible role of alcohol consumption and smoking were not considered. However, alco­hol consumption is not common in our population, but smoking was very common in men. There were no significant differences in SQ by gender in our study. Also, certain medications such as beta-blockers and statins may have influenced SQ, but the use of these drugs was not analyzed.

In conclusion, sleep disturbance was a com­mon problem in HD patients in our center, and this study showed that diabetes was the main predictor of poor SQ. As noted, the literature review found diverse and non-uniform results in demonstrating the predictors of SQ; how­ever, we cited studies with the same method and material for comparison. Perhaps this is due to the fact that, besides uremia and HD itself, sleep is under the influence of various other factors including different habits and behaviors, culture, economics and politics, and, to eliminate these confounding factors, further large-scale and multi-center studies are needed.

   Conclusion Top

Because of the high prevalence of sleep dis­orders among dialysis patients, especially among diabetics with its negative effect on quality of life, addressing this complaint is extremely important and it is reasonable to perform screening for sleep disorders as a routine for all patients on HD.

   References Top

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2.Walker S, Fine A, Kryger MH. Sleep com­plaints are common in a dialysis unit. Am J Kidney Dis 1995;26:751-6.  Back to cited text no. 2
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5.Unruh ML, Buysse DJ, Amanda MA, et al. Sleep quality and its correlates in the first year of dialysis. Clin J Am Soc Nephrol 2006;1: 802-10.  Back to cited text no. 5
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13.Benz RL, Pressman MR, Hovick ET, Peterson DD. Potential novel predictors of mortality in end-stage renal disease patients with sleep disorders. Am J Kidney Dis 2000;35:1052-60.  Back to cited text no. 13
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15.Iliescu E, Coo H, Mcmurray MH, et al. Quality of sleep and health-related quality of life in hemodialysis patients. Nephrol Dial Transplant 2003;18:126-32.  Back to cited text no. 15
16.Elder SJ, Pisoni RL, Akizawa T, et al. Sleep quality predicts quality of life and mortality risk in haemodialysis patients: Results from the dialysis outcomes and practice patterns study (dopps). Nephrol Dial Transplant 2008; 23:998-1004.  Back to cited text no. 16
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19.De Santo RM, Esposito MG, Cesare CM, et al. High prevalence of sleep disorders in hemo-dialyzed patients requiring parathyroidectomy. J Ren Nutr 2008;18:52-5.  Back to cited text no. 19
20.Esposito MG, Cesare CM, De Santo RM, et al. Parathyroidectomy improves the quality of sleep in maintenance hemodialysis patients with severe hyperparathyroidism. J Nephrol 2008;21 Suppl 13:S92-6.  Back to cited text no. 20
21.Chiu YL, Chuang YF, Fang KC, et al. Higher systemic inflammation is associated with poorer sleep quality in stable hemodialysis patients. Nephrol Dial Transplant 2009;24: 247-51.  Back to cited text no. 21
22.Buysse DJ, Reynolds CF 3rd, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: A new instrument for psychiatric practice and research. Psychiatry Res 1989;28:193-213.  Back to cited text no. 22

Correspondence Address:
Mahnaz Edalat-Nejad
Arak Medical Sciences University, Arak
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/1319-2442.134994

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  [Table 1], [Table 2], [Table 3], [Table 4]

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